ANN Modeling of Microstrip Hairpin-Line Bandpass Filter
DOI:
https://doi.org/10.18486/ijcsnt/3.1.034Keywords:
Microstrip Hairpin-Line Bandpass Filters, Coupling Coefficient, ANN model, MATLAB, IE3D EM Simulation, S-parameters, Training AlgorithmAbstract
In this paper a design technique for Hairpin-Line narrow band Microstrip Bandpass filters is presented by using the artificial neural network (ANN) modeling method at mid-band frequency 2.2 GHz for S-band applications which give minimum insertion loss (S21) of 0.2954 dB and maximum return loss of 27.4 dB in the passband. Consequently an artificial neural network model is developed to observe the Magnitude variation of scattering parameters (S-parameters) of Microstrip Band-pass filters at 2.2 GHz for different dimensions. The developed ANN model of microstrip band-pass filter is computationally more efficient in the design and the results are more accurate as compared to an Electromagnetic simulator. Essential dimensions of the microstrip filter layout are used to obtain the input-output relationships in the ANN model. The simulation and ANN training is performed using the commercial electromagnetic simulation software Zeland IE3D 14.1 and MATLAB programming language respectively.
References
Hong JSG and Lancaster MJ. Microstrip Filters for RF/Microwave Applications. 1 ed. John Wiley & Sons Inc., 2001. DOI: https://doi.org/10.1002/0471221619
Cohn SB. Parallel-coupled transmission-line-resonator filters. IRE Transactions on Microwave Theory and techniques 1958; MTT-6(4): 223–231. DOI: https://doi.org/10.1109/TMTT.1958.1124542
Cristal EG and Frankel S. Hairpin-line and hybrid hairpinline/half-wave parallel-coupled-line filters. IEEE Transactions on Microwave Theory and Techniques 1972; MTT-22(11): 719–728. DOI: https://doi.org/10.1109/TMTT.1972.1127860
Shamanna KN, Rao VS and Kosta SP. Design of parallel coupled microstrip band-pass filters. International Journal of Electronics 1978; 45(1): 89–96. DOI: https://doi.org/10.1080/00207217808900884
Kushwah VS, Tomar GS and Bhadoria SS. Optimum design of microstrip band stop filters using artificial neural network. International Journal of Communication Systems and Networks 2012; 1(2): 87–96. ISSN 2234-8018. DOI: https://doi.org/10.18486/ijcsnt/1.3.011
Kushwah VS and Tomar GS. Performance evaluation of ann model for the analysis of microstrip band pass filter. In IEEE International Conference on Computational Intelligence and Communication Systems. pp. 36–40. DOI: https://doi.org/10.1109/CICN.2010.18
Watson PM and Gupta KC. Em-ann models for microstrip vias and interconnects in dataset circuits. IEEE Trans Microwave Theory Tech 1996; 44: 2495–2503. DOI: https://doi.org/10.1109/22.554584
Bandler JW, Ismail MA, Rayas-Sanchez JE et al. Neuromodeling of microwave circuits exploiting space-mapping technology. IEEE Trans Microwave Theory Tech 1999; 47: 2417–2427. DOI: https://doi.org/10.1109/22.808989
Watson PM and Gupta KC. Design and optimization of cpw circuits using em-ann models for cpw components. IEEE Trans Microwave Theory Tech 1997; 45: 2515–2523. DOI: https://doi.org/10.1109/22.643868
Creech GL, Paul BJ, Lesniak CD et al. Artificial neural networks for fast and accurate em-cad of microwave circuits. IEEE Trans Microwave Theory Tech 1997; 45: 794–802. DOI: https://doi.org/10.1109/22.575602
Zaabab AH, Zhang QJ and Nakhla MS. A neural network modeling approach to circuit optimization and statistical design. IEEE Trans Microwave Theory Tech 1995; 43: 1349–1358. DOI: https://doi.org/10.1109/22.390193
Kushwah VS and Tomar GS. Design of microstrip patch antennas using neural network. The Icfai University journal of Science & Technology 2009; 5(2): 59–71. DOI: https://doi.org/10.1109/AMS.2009.12
Wang F, Devabhaktuni VK, Xi C et al. Neural Network Structures and Training Algorithms for RF and Microwave Applications. John Wiley & Sons, 1999. DOI: https://doi.org/10.1002/(SICI)1099-047X(199905)9:3<216::AID-MMCE7>3.0.CO;2-W
Li XP and Gao JJ. Millimeter-wave micromachined filter design by artificial neural network modeling technique. International Journal of Infrared and Millimeter Waves 2007; 28(7): 541–546. DOI: https://doi.org/10.1007/s10762-007-9227-7
Nath M and Gupta B. Analysis of em scattering in waveguide filter using neural network. International Journal of Electronics and Computer Science Engineering 2012; 1(2): 639–642. ISSN-2277-1956.
Kushwah VS, Tomar GS and Bhadauria SS. Designing stepped impedance microstrip lowpass filters using artificial neural network at 1.8 ghz. In IEEE International Conference on Communication Systems and Network Technologies. pp. 11–16. DOI: https://doi.org/10.1109/CSNT.2013.11
Tomar GS, Kushwah VS and Bhadauria SS. Artificial neural network design of stub microstrip band-pass filters. International Journal of Ultra-wideband Communication Systems, Inderscience publishers 2014; 3(1): 38–49. DOI: https://doi.org/10.1504/IJUWBCS.2014.060987
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